17 releases (3 stable)
Uses old Rust 2015
1.2.0 | Feb 15, 2023 |
---|---|
1.1.0 | Jun 1, 2022 |
1.0.0 | Mar 24, 2022 |
0.5.2 | Dec 13, 2021 |
0.3.1 | Jul 16, 2019 |
#83 in Math
1,653 downloads per month
Used in 3 crates
(2 directly)
41KB
1K
SLoC
hyperdual 
Fully-featured Dual Number implementation with features for automatic differentiation of multivariate vectorial functions into gradients.
Usage
extern crate hyperdual;
use hyperdual::{Dual, Hyperdual, Float, differentiate};
fn main() {
// find partial derivative at x=4.0
let univariate = differentiate(4.0f64, |x| x.sqrt() + Dual::from_real(1.0));
assert!((univariate - 0.4500).abs() < 1e-16, "wrong derivative");
// find the partial derivatives of a multivariate function
let x: Hyperdual<f64, 3> = Hyperdual::from_slice(&[4.0, 1.0, 0.0]);
let y: Hyperdual<f64, 3> = Hyperdual::from_slice(&[5.0, 0.0, 1.0]);
let multivariate = x * x + (x * y).sin() + y.powi(3);
assert!((res[0] - 141.91294525072763).abs() < 1e-13, "f(4, 5) incorrect");
assert!((res[1] - 10.04041030906696).abs() < 1e-13, "df/dx(4, 5) incorrect");
assert!((res[2] - 76.63232824725357).abs() < 1e-13, "df/dy(4, 5) incorrect");
}
Change log
Version 0.5.2
- Re-add support for nalgebra Owned Vectors for structures that do not yet support const generics.
Previous Work
Dependencies
~3MB
~57K SLoC